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The process of plant selection by insects is mediated by repellents and attractants. Several compounds may be involved in this interaction. Thus intraspecific variation of the compounds concentration play an important role in the herbivory. The best tool for the characteristic of this variation is chemometrics. The strategy of the analysis with the use of literature data on terpenes and sesquiterpenes variations in Pinus caribaea needles in relation to Atta laevigata herbivory is exemplified herein. Simple cluster analysis and principal components analysis were used for the data study. Two factors were found to be sufficient to describe total variation in more than 90%. Factor 1 is responsible for repellent properties. From factor loading, the relevant chemical compounds were identified.
The synergistic effect of ammonium polyphosphate (APP) and boric acid (BA) on the flame retardancy and thermal degradation of pine needles was investigated. Thermogravimetric analysis (TGA) showed that the presence of an ammoniumpolyphosphate and boric acid system increased the char residue and decreased the pyrolysis temperature of the pine needles. The derivative thermogravimetric analysis (DTG) showed that the ammonium polyphosphate and boric acid had shifted the degradation peaks of the pine needles to lower temperatures. The cone calorimetry test results showed that the values of HRR, THR, SPR, TSP and the mass loss (%) of the pine needles treated with ammonium polyphosphate and boric acid (APP/BA = 3/2)were significantly lower than the other samples. Therefore, the APP and BA system had a better effect on the pine needles overall than the APP alone.
The distribution of polycyclic aromatic hydrocarbons (PAHs) in plant and organic soil from 14 peatland sites in NE Poland and 7 peatland sites in SE Poland have been investigated. The total PAH concentration in the leaves of Ledum palustre collected from peatlands in NE Poland ranged from 232 ng/g to 1523 ng/g and was higher than the total PAH concentration in pine needles (Pinus sylvestris) taken from those same peatlands (the values ranged from 181 to307 ng/g). A similar trend was observed in the case of plants from the peatlands in SE Poland, except that the overall PAH concentration in the majority of the plant samples was found to be higher than those found in NE Poland. Phenanthrene and fluoranthene had the biggest share in the overall PAH concentration in all the peat and plant samples. The lack of 5- and 6-ringed PAHs in the plant and soil material indicates the lack of any direct emission sources of these compounds in regions adjacent to those examined in the study. Total sum of PAH pollution levels in peats and plants as well as vertical distribution of the concentrations in the soil profile of particular study sites integrates long-range pollution sources. To compare natural and antropogenic PAH input in the pealtlands, we have used parent PAH ratios: ANT/(ANT&PHE); FLT/(FLT&PYR). Our data suggest that PAHs with four and more rings do not allow a simple segregation into combustion or petroleum sources.
63 congeners of chloronaphthalene represented by 53 peaks fractionated and separated using two-dimensional HPLC and DB-17 capillary column were quantified using HRMS in ten samples of pine needles collected in 1999 around Tokyo Bay in Japan. Similarities and differences of chloronaphthalene concentrations and patterns between 10 sampling sites were studied using multivariate analysis. Total PCN concentrations ranged from 250 to 2100 pg/g wet weight. Except for one site, tri- and tetra-CNs highly dominated (from 54 to 80%) in CN homologue patterns of pine needles. At the easternmost site near the town of Tateyama in Chiba Prefecture the contribution from octaCN was ~20 %, while that of tri- and tetra-CNs ~42 %. Pine needles sampled from the sites around the innermost part of Tokyo Bay showed the highest load of PCNs. A multivariate analysis using the three most significant principal components explained 91% of the total variance in the measurement data. The greatest positive loading to PC1 is from the CN congeners nos. 13, 14/21/24, 15, 16, 17, 18, 19, 20, 22/23, 25, 26, 27, 28/36, 29, 30/32, 31, 33/34/37, 35, 40, 42, 43/45, 44, 47, 49, 50, 51, 52/60, 53, 57, 58, 59, 61, 62, 64, 65, 66/67, 68, 69, 71 and 72, and explains 65% variance in the data set. For PC2 the largest positive loading is from CNs nos.74 and 75, and negative load from CN nos. 38, 41, 46 and 48, which explains 17% of the variance. In case of PC3 the largest negative load is from CNs nos. 54, 56, 63, 70 and 73. A profile of the combustion process related CN congeners measured such as nos. 44, 48 and 54 didn’t show any specific trend implying pollution from diffused sources of various types.
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